健康状况
荷电状态
电池(电)
计算机科学
降级(电信)
控制理论(社会学)
电子工程
工程类
功率(物理)
人工智能
量子力学
物理
控制(管理)
作者
Guangfeng Wang,Naxin Cui,Changlong Li,Zhongrui Cui,Haitao Yuan
标识
DOI:10.1016/j.est.2023.109010
摘要
Incremental capacity analysis (ICA) is an effective method for analyzing the degradation mechanism and estimating the state of health (SOH) of lithium-ion batteries. However, the incremental capacity (IC) curve is sensitive to the initial state of charge (SOC) and the charging/discharging rate (CDR), which will lead to the deformation of the IC curve and the displacement of the health feature. In this paper, an ICA-based SOH estimation method that considers the charging/discharging rate is proposed, which can achieve accurate SOH estimation. Furthermore, a method for quickly obtaining a smooth IC curve based on finite-time differentiator is developed, which realizes the online processing of high-frequency sampling data. Experiments with different initial SOCs and charging/discharging rates were designed and performed. The degradation data during standard charging are used to construct the mapping relationship between the health feature and SOH. Considering different initial SOCs, health features without being affected by different charging/discharging rates are selected for SOH estimation. The validation results show that the SOH estimation errors are within 3% for batteries at different aging levels.
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